R version 2.8.0 (2008-10-20) Copyright (C) 2008 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. Natural language support but running in an English locale R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(235.1 + ,1 + ,280.7 + ,1 + ,264.6 + ,2 + ,240.7 + ,0 + ,201.4 + ,1 + ,240.8 + ,0 + ,241.1 + ,-1 + ,223.8 + ,-3 + ,206.1 + ,-3 + ,174.7 + ,-3 + ,203.3 + ,-4 + ,220.5 + ,-8 + ,299.5 + ,-9 + ,347.4 + ,-13 + ,338.3 + ,-18 + ,327.7 + ,-11 + ,351.6 + ,-9 + ,396.6 + ,-10 + ,438.8 + ,-13 + ,395.6 + ,-11 + ,363.5 + ,-5 + ,378.8 + ,-15 + ,357 + ,-6 + ,369 + ,-6 + ,464.8 + ,-3 + ,479.1 + ,-1 + ,431.3 + ,-3 + ,366.5 + ,-4 + ,326.3 + ,-6 + ,355.1 + ,0 + ,331.6 + ,-4 + ,261.3 + ,-2 + ,249 + ,-2 + ,205.5 + ,-6 + ,235.6 + ,-7 + ,240.9 + ,-6 + ,264.9 + ,-6 + ,253.8 + ,-3 + ,232.3 + ,-2 + ,193.8 + ,-5 + ,177 + ,-11 + ,213.2 + ,-11 + ,207.2 + ,-11 + ,180.6 + ,-10 + ,188.6 + ,-14 + ,175.4 + ,-8 + ,199 + ,-9 + ,179.6 + ,-5 + ,225.8 + ,-1 + ,234 + ,-2 + ,200.2 + ,-5 + ,183.6 + ,-4 + ,178.2 + ,-6 + ,203.2 + ,-2 + ,208.5 + ,-2 + ,191.8 + ,-2 + ,172.8 + ,-2 + ,148 + ,2 + ,159.4 + ,1 + ,154.5 + ,-8 + ,213.2 + ,-1 + ,196.4 + ,1 + ,182.8 + ,-1 + ,176.4 + ,2 + ,153.6 + ,2 + ,173.2 + ,1 + ,171 + ,-1 + ,151.2 + ,-2 + ,161.9 + ,-2 + ,157.2 + ,-1 + ,201.7 + ,-8 + ,236.4 + ,-4 + ,356.1 + ,-6 + ,398.3 + ,-3 + ,403.7 + ,-3 + ,384.6 + ,-7 + ,365.8 + ,-9 + ,368.1 + ,-11 + ,367.9 + ,-13 + ,347 + ,-11 + ,343.3 + ,-9 + ,292.9 + ,-17 + ,311.5 + ,-22 + ,300.9 + ,-25 + ,366.9 + ,-20 + ,356.9 + ,-24 + ,329.7 + ,-24 + ,316.2 + ,-22 + ,269 + ,-19 + ,289.3 + ,-18 + ,266.2 + ,-17 + ,253.6 + ,-11 + ,233.8 + ,-11 + ,228.4 + ,-12 + ,253.6 + ,-10 + ,260.1 + ,-15 + ,306.6 + ,-15 + ,309.2 + ,-15 + ,309.5 + ,-13 + ,271 + ,-8 + ,279.9 + ,-13 + ,317.9 + ,-9 + ,298.4 + ,-7 + ,246.7 + ,-4 + ,227.3 + ,-4 + ,209.1 + ,-2) + ,dim=c(2 + ,106) + ,dimnames=list(c('Werkloosheid' + ,'Consumentenvertrouwen') + ,1:106)) > y <- array(NA,dim=c(2,106),dimnames=list(c('Werkloosheid','Consumentenvertrouwen'),1:106)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par4 = 'no' > par3 = '2' > par2 = 'quantiles' > par1 = '1' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Dr. Ian E. Holliday > #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from package:survival : untangle.specials The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "Werkloosheid" > x[,par1] [1] 235.1 280.7 264.6 240.7 201.4 240.8 241.1 223.8 206.1 174.7 203.3 220.5 [13] 299.5 347.4 338.3 327.7 351.6 396.6 438.8 395.6 363.5 378.8 357.0 369.0 [25] 464.8 479.1 431.3 366.5 326.3 355.1 331.6 261.3 249.0 205.5 235.6 240.9 [37] 264.9 253.8 232.3 193.8 177.0 213.2 207.2 180.6 188.6 175.4 199.0 179.6 [49] 225.8 234.0 200.2 183.6 178.2 203.2 208.5 191.8 172.8 148.0 159.4 154.5 [61] 213.2 196.4 182.8 176.4 153.6 173.2 171.0 151.2 161.9 157.2 201.7 236.4 [73] 356.1 398.3 403.7 384.6 365.8 368.1 367.9 347.0 343.3 292.9 311.5 300.9 [85] 366.9 356.9 329.7 316.2 269.0 289.3 266.2 253.6 233.8 228.4 253.6 260.1 [97] 306.6 309.2 309.5 271.0 279.9 317.9 298.4 246.7 227.3 209.1 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$centers,1:par3),ncol=2) + clm <- clm[sort.list(clm[,1]),] + for (i in 1:par3) { + cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='') + } + cl$cluster <- as.factor(cl$cluster) + print(cl$cluster) + x[,par1] <- cl$cluster + } > if (par2 == 'quantiles') { + x[,par1] <- cut2(x[,par1],g=par3) + } > if (par2 == 'hclust') { + hc <- hclust(dist(x[,par1])^2, 'cen') + print(hc) + memb <- cutree(hc, k = par3) + dum <- c(mean(x[memb==1,par1])) + for (i in 2:par3) { + dum <- c(dum, mean(x[memb==i,par1])) + } + hcm <- matrix(cbind(dum,1:par3),ncol=2) + hcm <- hcm[sort.list(hcm[,1]),] + for (i in 1:par3) { + memb[memb==hcm[i,2]] <- paste('C',i,sep='') + } + memb <- as.factor(memb) + print(memb) + x[,par1] <- memb + } > if (par2=='equal') { + ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep='')) + x[,par1] <- as.factor(ed) + } > table(x[,par1]) [148,254) [254,479] 53 53 > colnames(x) [1] "Werkloosheid" "Consumentenvertrouwen" > colnames(x)[par1] [1] "Werkloosheid" > x[,par1] [1] [148,254) [254,479] [254,479] [148,254) [148,254) [148,254) [148,254) [8] [148,254) [148,254) [148,254) [148,254) [148,254) [254,479] [254,479] [15] [254,479] [254,479] [254,479] [254,479] [254,479] [254,479] [254,479] [22] [254,479] [254,479] [254,479] [254,479] [254,479] [254,479] [254,479] [29] [254,479] [254,479] [254,479] [254,479] [148,254) [148,254) [148,254) [36] [148,254) [254,479] [254,479] [148,254) [148,254) [148,254) [148,254) [43] [148,254) [148,254) [148,254) [148,254) [148,254) [148,254) [148,254) [50] [148,254) [148,254) [148,254) [148,254) [148,254) [148,254) [148,254) [57] [148,254) [148,254) [148,254) [148,254) [148,254) [148,254) [148,254) [64] [148,254) [148,254) [148,254) [148,254) [148,254) [148,254) [148,254) [71] [148,254) [148,254) [254,479] [254,479] [254,479] [254,479] [254,479] [78] [254,479] [254,479] [254,479] [254,479] [254,479] [254,479] [254,479] [85] [254,479] [254,479] [254,479] [254,479] [254,479] [254,479] [254,479] [92] [254,479] [148,254) [148,254) [254,479] [254,479] [254,479] [254,479] [99] [254,479] [254,479] [254,479] [254,479] [254,479] [148,254) [148,254) [106] [148,254) Levels: [148,254) [254,479] > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > if (par2 != 'none') { + m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x) + if (par4=='yes') { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'',1,TRUE) + a<-table.element(a,'Prediction (training)',par3+1,TRUE) + a<-table.element(a,'Prediction (testing)',par3+1,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Actual',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE) + a<-table.element(a,'CV',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE) + a<-table.element(a,'CV',1,TRUE) + a<-table.row.end(a) + for (i in 1:10) { + ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1)) + m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,]) + if (i==1) { + m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,]) + m.ct.i.actu <- x[ind==1,par1] + m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,]) + m.ct.x.actu <- x[ind==2,par1] + } else { + m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,])) + m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1]) + m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,])) + m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1]) + } + } + print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred)) + numer <- 0 + for (i in 1:par3) { + print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,])) + numer <- numer + m.ct.i.tab[i,i] + } + print(m.ct.i.cp <- numer / sum(m.ct.i.tab)) + print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred)) + numer <- 0 + for (i in 1:par3) { + print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,])) + numer <- numer + m.ct.x.tab[i,i] + } + print(m.ct.x.cp <- numer / sum(m.ct.x.tab)) + for (i in 1:par3) { + a<-table.row.start(a) + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj]) + a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4)) + for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj]) + a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4)) + a<-table.row.end(a) + } + a<-table.row.start(a) + a<-table.element(a,'Overall',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,'-') + a<-table.element(a,round(m.ct.i.cp,4)) + for (jjj in 1:par3) a<-table.element(a,'-') + a<-table.element(a,round(m.ct.x.cp,4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/html/freestat/rcomp/tmp/12gu41291990361.tab") + } + } > m Conditional inference tree with 2 terminal nodes Response: as.factor(Werkloosheid) Input: Consumentenvertrouwen Number of observations: 106 1) Consumentenvertrouwen <= -9; criterion = 1, statistic = 26.877 2)* weights = 40 1) Consumentenvertrouwen > -9 3)* weights = 66 > postscript(file="/var/www/html/freestat/rcomp/tmp/22gu41291990361.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(m) > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/32gu41291990361.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response') > dev.off() null device 1 > if (par2 == 'none') { + forec <- predict(m) + result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec)) + colnames(result) <- c('Actuals','Forecasts','Residuals') + print(result) + } > if (par2 != 'none') { + print(cbind(as.factor(x[,par1]),predict(m))) + myt <- table(as.factor(x[,par1]),predict(m)) + print(myt) + } [,1] [,2] [1,] 1 1 [2,] 2 1 [3,] 2 1 [4,] 1 1 [5,] 1 1 [6,] 1 1 [7,] 1 1 [8,] 1 1 [9,] 1 1 [10,] 1 1 [11,] 1 1 [12,] 1 1 [13,] 2 2 [14,] 2 2 [15,] 2 2 [16,] 2 2 [17,] 2 2 [18,] 2 2 [19,] 2 2 [20,] 2 2 [21,] 2 1 [22,] 2 2 [23,] 2 1 [24,] 2 1 [25,] 2 1 [26,] 2 1 [27,] 2 1 [28,] 2 1 [29,] 2 1 [30,] 2 1 [31,] 2 1 [32,] 2 1 [33,] 1 1 [34,] 1 1 [35,] 1 1 [36,] 1 1 [37,] 2 1 [38,] 2 1 [39,] 1 1 [40,] 1 1 [41,] 1 2 [42,] 1 2 [43,] 1 2 [44,] 1 2 [45,] 1 2 [46,] 1 1 [47,] 1 2 [48,] 1 1 [49,] 1 1 [50,] 1 1 [51,] 1 1 [52,] 1 1 [53,] 1 1 [54,] 1 1 [55,] 1 1 [56,] 1 1 [57,] 1 1 [58,] 1 1 [59,] 1 1 [60,] 1 1 [61,] 1 1 [62,] 1 1 [63,] 1 1 [64,] 1 1 [65,] 1 1 [66,] 1 1 [67,] 1 1 [68,] 1 1 [69,] 1 1 [70,] 1 1 [71,] 1 1 [72,] 1 1 [73,] 2 1 [74,] 2 1 [75,] 2 1 [76,] 2 1 [77,] 2 2 [78,] 2 2 [79,] 2 2 [80,] 2 2 [81,] 2 2 [82,] 2 2 [83,] 2 2 [84,] 2 2 [85,] 2 2 [86,] 2 2 [87,] 2 2 [88,] 2 2 [89,] 2 2 [90,] 2 2 [91,] 2 2 [92,] 2 2 [93,] 1 2 [94,] 1 2 [95,] 2 2 [96,] 2 2 [97,] 2 2 [98,] 2 2 [99,] 2 2 [100,] 2 1 [101,] 2 2 [102,] 2 2 [103,] 2 1 [104,] 1 1 [105,] 1 1 [106,] 1 1 [148,254) [254,479] [148,254) 45 8 [254,479] 21 32 > postscript(file="/var/www/html/freestat/rcomp/tmp/4nysa1291990361.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > if(par2=='none') { + op <- par(mfrow=c(2,2)) + plot(density(result$Actuals),main='Kernel Density Plot of Actuals') + plot(density(result$Residuals),main='Kernel Density Plot of Residuals') + plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals') + plot(density(result$Forecasts),main='Kernel Density Plot of Predictions') + par(op) + } > if(par2!='none') { + plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted') + } > dev.off() null device 1 > if (par2 == 'none') { + detcoef <- cor(result$Forecasts,result$Actuals) + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goodness of Fit',2,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Correlation',1,TRUE) + a<-table.element(a,round(detcoef,4)) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'R-squared',1,TRUE) + a<-table.element(a,round(detcoef*detcoef,4)) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'RMSE',1,TRUE) + a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/html/freestat/rcomp/tmp/5qh9y1291990361.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'#',header=TRUE) + a<-table.element(a,'Actuals',header=TRUE) + a<-table.element(a,'Forecasts',header=TRUE) + a<-table.element(a,'Residuals',header=TRUE) + a<-table.row.end(a) + for (i in 1:length(result$Actuals)) { + a<-table.row.start(a) + a<-table.element(a,i,header=TRUE) + a<-table.element(a,result$Actuals[i]) + a<-table.element(a,result$Forecasts[i]) + a<-table.element(a,result$Residuals[i]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/freestat/rcomp/tmp/6ch7m1291990361.tab") + } > if (par2 != 'none') { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'',1,TRUE) + for (i in 1:par3) { + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + } + a<-table.row.end(a) + for (i in 1:par3) { + a<-table.row.start(a) + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + for (j in 1:par3) { + a<-table.element(a,myt[i,j]) + } + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/freestat/rcomp/tmp/749761291990361.tab") + } > > try(system("convert tmp/22gu41291990361.ps tmp/22gu41291990361.png",intern=TRUE)) character(0) > try(system("convert tmp/32gu41291990361.ps tmp/32gu41291990361.png",intern=TRUE)) character(0) > try(system("convert tmp/4nysa1291990361.ps tmp/4nysa1291990361.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.392 0.661 3.652